This is my collection of helpful priming prompts for ChatGPT, or other LLMs, when discussing various angles of software development and architecture.
This is targetted as a "living dialogue" with heavier interaction between both parties. You'll get lots of follow-up proposals and diagrams and code examples.
We are struggling with understanding how to apply the "branching by abstraction" notion to our serverless functions. Currently, we have lots of integration issues and have no API versioning. We want to use this pattern to evolve and increase the stability.This is a great way to get feedback on a digitally-generated diagram.
You will have to use an LLM that can take image input.
For a cheap, fast, helpful code review, you can use an LLM. Even better, set it up with your own policy of things you care about!
It's common to draw architecture diagrams on paper or on a whiteboard. Let the LLM do the majority of work by converting your drawing into a formal, digital diagram.
Make sure to explain the context well, and to draw cleanly.
You will have to use an LLM that can take image input.
Here we are expecting a discussion around specific performance issues in our team, using DORA data or (if modified) our overall issues. This will address both cultural and technical issues.
Our current DORA metrics (spanning a 30 day period) are:
- Change failure rate: 3%
- Deployment frequency: 3.12 per day
- Lead time for changes: 7 minutes
- Mean time to recover: 104 minutesThis one is all about getting concrete advice on problems a formal analysis has uncovered. It will prioritize and explain why certain activities should get more attention than other. It also helps with adapting the language to non-technical users.
Run a HealthCheck review and export the results as CSV. This won't be 100% exact when using with ChatGPT due to the structure of the document but it should be able to give you a good start.
To scaffold your integration test suite, just ask the LLM to setup the critical tests based on your API schema.